-
Notifications
You must be signed in to change notification settings - Fork 0
added chord to run multiple tasks in parallel, in that way I distribu… #22
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Conversation
…te one big task into 10 subtasks
Summary of ChangesHello @LuisJG8, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed! This pull request significantly enhances the system's ability to process large datasets by implementing a robust parallel task execution strategy using Celery chords. It refactors the task distribution mechanism to break down a single large data retrieval operation into smaller, concurrently executable subtasks, followed by an automated aggregation of their results. This change aims to improve scalability and efficiency when fetching data, particularly from external APIs like GitHub. Highlights
🧠 New Feature in Public Preview: You can now enable Memory to help Gemini Code Assist learn from your team's feedback. This makes future code reviews more consistent and personalized to your project's style. Click here to enable Memory in your admin console. Using Gemini Code AssistThe full guide for Gemini Code Assist can be found on our documentation page, here are some quick tips. Invoking Gemini You can request assistance from Gemini at any point by creating a comment using either
Customization To customize Gemini Code Assist for GitHub experience, repository maintainers can create a configuration file and/or provide a custom code review style guide (such as PEP-8 for Python) by creating and adding files to a Limitations & Feedback Gemini Code Assist may make mistakes. Please leave feedback on any instances where its feedback is incorrect or counter productive. You can react with 👍 and 👎 on @gemini-code-assist comments. If you're interested in giving your feedback about your experience with Gemini Code Assist for Github and other Google products, sign up here. You can also get AI-powered code generation, chat, as well as code reviews directly in the IDE at no cost with the Gemini Code Assist IDE Extension. Footnotes
|
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Code Review
This pull request refactors the task distribution logic to use Celery's chord primitive for parallel execution of subtasks and result aggregation. This is a good approach for distributing a large workload. My review includes a critical fix for a bug in the batching logic where a hardcoded value was used instead of the batch_size parameter. I've also pointed out some minor code cleanup opportunities, such as removing temporary test comments and suggesting the use of constants for hardcoded values to improve maintainability.
|
|
||
| if int(counter) == 10: | ||
| print(f"Reached the rate limit of {rate_limit[1]} API calls") | ||
| if int(counter) >= int(2): |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
This condition appears to contain a hardcoded value 2 from testing or debugging, which will cause the task to process at most 2 repositories regardless of the batch_size. It should use the batch_size parameter to correctly limit the number of repositories processed per task. Also, casting counter to int is redundant as it's already an integer.
| if int(counter) >= int(2): | |
| if counter >= batch_size: |
|
|
||
| print("Waiting for Celery task to complete") | ||
|
|
||
| # test |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
| try: | ||
| print("Getting the result") | ||
| response = distribute_tasks.apply_async() | ||
| response = build_repo_chord(total=5000, batch_size=500) |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
| # the way groups can be linked is by usign the chord construct in Celery, | ||
| # this is important when the groups have an order | ||
| # groups, chords | ||
| # test |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
…te one big task into 10 subtasks